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A Novel Fermentation Control Method Based on Neural Networks

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Advances in Neural Networks - ISNN 2004 (ISNN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3174))

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Abstract

This paper proposes a novel fermentation control method. Two stages are involved. First, propose the fermentation time model and the optimal fermentation temperature model based on RBF Neural networks. Second, on the base of the two models, propose the novel fermentation control method by which different fermentation batch can adopt different optimal fermentation temperature trajectory which fits itself. Using this method, each fermentation batch can be fermented at optimal fermentation temperature trajectory and will improve average product proportion. The practical application showed that this method can improve average product proportion 3% effectively.

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References

  1. Leal Ascencio, R.R., Reynaga, F., Herrera, E., Gschaedler, A.: Artificial neural networks as a biomass virtual sensor for a batch process. In: Proceedings of the 2001 IEEE International Symposium on Intelligent Control, pp. 246–251 (2001)

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© 2004 Springer-Verlag Berlin Heidelberg

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Yang, X., Sun, Z., Sun, Y. (2004). A Novel Fermentation Control Method Based on Neural Networks. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_30

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  • DOI: https://doi.org/10.1007/978-3-540-28648-6_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22843-1

  • Online ISBN: 978-3-540-28648-6

  • eBook Packages: Springer Book Archive

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